{"id":"W2163744424","doi":"10.1007/s10144-008-0088-2","title":"Interlinking hare and lynx dynamics using a century's worth of annual data","year":2008,"lang":"en","type":"article","venue":"Population Ecology","topic":"Wildlife Ecology and Conservation","field":"Environmental Science","cited_by":25,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"Universitetet i Oslo","keywords":"Abundance (ecology); Ecology; Bay; Snowshoe hare; Intraspecific competition; Population; Biology; Relative species abundance; Geography; Predation; Demography","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001208379,0.00005694735,0.0001030991,0.00003193849,0.0001259167,0.000002141289,0.0001234876,0.00008297146,0.0002790526],"category_scores_gemma":[0.00007067899,0.00006087872,0.000009722181,0.0000905104,0.0001159712,0.0002950811,0.0002383859,0.00006263726,0.000009966949],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000751445,"about_ca_system_score_gemma":0.000008208494,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003944811,"about_ca_topic_score_gemma":0.005157165,"domain_scores_codex":[0.9993992,0.00005117221,0.0001861905,0.0001912372,0.00005861619,0.0001135124],"domain_scores_gemma":[0.9996231,0.00004133685,0.0001258103,0.0001766657,0.000007978247,0.00002507791],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000009780563,0.0000220693,0.9970675,0.000002619764,0.000004883395,0.000002735663,0.0002142781,0.0006603966,0.000005534136,0.0000994584,0.00009458765,0.001816216],"study_design_scores_gemma":[0.0001340975,0.00002363786,0.9246954,0.000002674965,0.000008673484,0.00002466922,0.00008003882,0.07467252,0.000001121697,0.0002314298,0.00007329309,0.000052388],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.998701,0.00001100348,0.0006812056,0.0002220584,0.0001532649,0.00008514082,0.00003217514,0.00001300291,0.0001011915],"genre_scores_gemma":[0.9977968,0.00001250858,0.001691407,0.0002150784,0.00001848115,0.000001582435,0.0002305975,0.000004727469,0.00002881116],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.07401212,"threshold_uncertainty_score":0.3055431,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03221736645632854,"score_gpt":0.2546768422859219,"score_spread":0.2224594758295934,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}